---
title: "From POC to Production. Navigating GenAI Implementation in Life Sciences"
description: ""
url: "https://pmsa.org/webinars/webinar-archive/item/from-poc-to-production-navigating-genai-implementation-in-life-sciences"
date: "2026-06-14T21:23:49+00:00"
language: "en-GB"
---

#  From POC to Production. Navigating GenAI Implementation in Life Sciences

### Description

Generative AI (GenAI) is revolutionizing the life sciences industry, with innovative proofs of concept (POCs) and use cases emerging rapidly. The opportunity now lies in determining how to advance these innovations to production, achieve scale, and create meaningful impact.

We’ve analyzed GenAI projects across the pharma and biotech industries and identified six key opportunity areas for teams to address in order to make AI a significant value driver within their organizations.

Join BeiGene and Beghou experts for concrete examples and actionable approaches for:

- Kickstarting GenAI implementation and prioritizing use cases to build momentum
- Building a strong tech foundation with optimal data infrastructure
- Ensuring high data quality, privacy, and input accuracy
    Monitoring and improving the model to ensure high performance and responsible AI principles
- Navigating change management and enabling ownership
- Moving GenAI forward while stabilizing what’s already been built

### Sponsored by:

Beghou Consulting

### Back to:

[Webinars](https://pmsa.org/webinars/webinar-archive) | [Beghou Consulting](https://pmsa.org/webinars/webinar-archive/category/beghou-consulting)

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    "description": "Generative AI (GenAI) is revolutionizing the life sciences industry, with innovative proofs of concept (POCs) and use cases emerging rapidly. The opportunity now lies in determining how to advance these innovations to production, achieve scale, and create meaningful impact. We’ve analyzed GenAI projects across the pharma and biotech industries and identified six key opportunity areas for teams to address in order to make AI a significant value driver within their organizations. Join BeiGene and Beghou experts for concrete examples and actionable approaches for:  Kickstarting GenAI implementation and prioritizing use cases to build momentum Building a strong tech foundation with optimal data infrastructure Ensuring high data quality, privacy, and input accuracy Monitoring and improving the model to ensure high performance and responsible AI principles Navigating change management and enabling ownership Moving GenAI forward while stabilizing what’s already been built ",
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